Characterizing non-linear dependencies among pairs of clinical variables and imaging data

Jesus J. Caban, Ulas Bagci, Alem Mehari, Shoaib Alam, Joseph R. Fontana, Gregory J. Kato, Daniel J. Mollura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Advances in computer-aided diagnosis (CAD) systems have shown the benefits of using computer-based techniques to obtain quantitative image measurements of the extent of a particular disease. Such measurements provide more accurate information that can be used to better study the associations between anatomical changes and clinical findings. Unfortunately, even with the use of quantitative image features, the correlations between anatomical changes and clinical findings are often not apparent and definite conclusions are difficult to reach. This paper uses nonparametric exploration techniques to demonstrate that even when the associations between two-variables seems weak, advanced properties of the associations can be studied and used to better understand the relationships between individual measurements. This paper uses quantitative imaging findings and clinical measurements of 85 patients with pulmonary fibrosis to demonstrate the advantages of non-linear dependency analysis. Results show that even when the correlation coefficients between imaging and clinical findings seem small, statistical measurements such as the maximum asymmetry score (MAS) and maximum edge value (MEV) can be used to better understand the hidden associations between the variables

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages2700-2703
Number of pages4
DOIs
StatePublished - Dec 14 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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